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DBMS > Fauna vs. Google Cloud Datastore vs. Manticore Search vs. Microsoft Azure AI Search

System Properties Comparison Fauna vs. Google Cloud Datastore vs. Manticore Search vs. Microsoft Azure AI Search

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Editorial information provided by DB-Engines
NameFauna infopreviously named FaunaDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonManticore Search  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparison
DescriptionFauna provides a web-native interface, with support for GraphQL and custom business logic that integrates seamlessly with the rest of the serverless ecosystem. The underlying globally distributed storage and compute platform is fast, consistent, and reliable, with a modern security infrastructure.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformMulti-storage database for search, including full-text search.Search-as-a-service for web and mobile app development
Primary database modelDocument store
Graph DBMS
Relational DBMS
Time Series DBMS
Document storeSearch engineSearch engine
Secondary database modelsTime Series DBMS infousing the Manticore Columnar LibraryVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.52
Rank#153  Overall
#26  Document stores
#14  Graph DBMS
#71  Relational DBMS
#13  Time Series DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score0.22
Rank#312  Overall
#21  Search engines
Score5.59
Rank#63  Overall
#7  Search engines
Websitefauna.comcloud.google.com/­datastoremanticoresearch.comazure.microsoft.com/­en-us/­services/­search
Technical documentationdocs.fauna.comcloud.google.com/­datastore/­docsmanual.manticoresearch.comlearn.microsoft.com/­en-us/­azure/­search
DeveloperFauna, Inc.GoogleManticore SoftwareMicrosoft
Initial release2014200820172015
Current release6.0, February 2023V1
License infoCommercial or Open SourcecommercialcommercialOpen Source infoGPL version 2commercial
Cloud-based only infoOnly available as a cloud serviceyesyesnoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageScalaC++
Server operating systemshostedhostedFreeBSD
Linux
macOS
Windows
hosted
Data schemeschema-freeschema-freeFixed schemayes
Typing infopredefined data types such as float or datenoyes, details hereInt, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Booleanyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nonoCan index from XMLno
Secondary indexesyesyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLnoSQL-like query language (GQL)SQL-like query languageno
APIs and other access methodsRESTful HTTP APIgRPC (using protocol buffers) API
RESTful HTTP/JSON API
Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL
RESTful HTTP API
Supported programming languagesC#
Go
Java
JavaScript
Python
Ruby
Scala
Swift
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
C#
Java
JavaScript
Python
Server-side scripts infoStored proceduresuser defined functionsusing Google App Engineuser defined functionsno
TriggersnoCallbacks using the Google Apps Enginenono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning infoconsistent hashingShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationMulti-source replication using PaxosSynchronous replication based on Galera libraryyes infoImplicit feature of the cloud service
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate Consistency
Foreign keys infoReferential integrityyesyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsyes infoisolated transactions for atomic changes and binary logging for safe writesno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoThe original contents of fields are not stored in the Manticore index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlIdentity management, authentication, and access controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noyes infousing Azure authentication

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More resources
Fauna infopreviously named FaunaDBGoogle Cloud DatastoreManticore SearchMicrosoft Azure AI Search
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